Sanction teardown · Upper Tribunal, UK · 2025-11-17
UK and R (Munir) v Secretary of State for the Home Department
What happened
In Upper Tribunal, UK, a filing relied on an unnamed/unconfirmed AI tool to help draft legal argument. The court identified the following problems with the citations in that filing:
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Fabricated (Case Law)A non-existent case 'Horleston' was included in the grounds; the Tribunal found no reported case and demonstrated that Google AI can fabricate bench details—solicitor concluded it was probably AI-generated.
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Misrepresented (Case Law)R (Dzineku-Liggison) v SSHD was cited with a High Court citation that does not exist; the correct authority is an Upper Tribunal decision.
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Misrepresented (Case Law)A decision labelled 'Patel (mandatory refusal – fairness)' was cited as a Court of Appeal decision though the correct report is an Upper Tribunal decision.
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Misrepresented (Case Law)Muhandiramge was cited with an Administrative Court citation that the Panel could not locate; the relevant reported decision is an Upper Tribunal decision with a different date and citation.
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Misrepresented (Case Law)A case referred to as OE (Nigeria) with citation [2010] UKUT 35 (IAC) could not be found; the matter appears to correspond to a differently titled Upper Tribunal decision.
Which AI tool
an unnamed/unconfirmed AI tool. Note: Charlotin's public database records tool attribution only where a court order, brief, or reporting on the matter states it explicitly; "unidentified" or "implied" means the record indicates AI use but does not name a specific product — we do not guess.
Outcome
Bar Referral
How Citation Safe would have caught this
Citation Safe runs three deterministic layers before a brief is filed: (1) does the citation exist against CourtListener's database of published opinions, (2) if quoted, does that exact language appear in the source, (3) does the cited case actually support the proposition it is cited for. Fabricated case citations fail Layer 1. Fabricated or misattributed quotations fail Layer 2 even when the underlying case is real. Misrepresented holdings — a real case cited for a proposition it does not support — are the target of Layer 3. None of these checks involve asking another language model whether the citation looks right; they are lookups and text-matches against the actual source, which is why a hallucinated citation has to survive a direct lookup against the authoritative source — not another model's opinion — to earn a VERIFIED stamp; our measured false-verify rate is published live at /quality.
Check a brief before you file it → · See our live false-verify rate
Source: https://www.damiencharlotin.com/documents/1565/Munir_v._SSHD_UK_17_November_2025.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).